The present disclosure relates to management of image data in electronic video systems and, in particular, to management of image display for rendering on a variety of display devices.
Modern display devices vary in the brightness, color gamut and dynamic range of the images that they can render. Cathode ray tube (commonly, “CRT”) displays commonly are rated at ˜100 nits (100 candelas per square meter), while LCD displays for residential and office-based applications may be rated at ˜400 nits. Still other displays, such as LCD-based billboard displays may be rated at higher levels. And research efforts are underway to develop new display technologies in the range till 10,000 nits.
Moreover, image processing applications are generating image data at higher dynamic ranges. Where image data values may have been defined using 8 or 10 bit depth color values, newer image processing applications are generating such image data values at 12 or perhaps 16 bit values. The increasing dynamic range permits image content to be rendered at finer quantization levels than before. And, of course, different display devices may support different dynamic ranges.
Additionally, viewing conditions may vary considerably. In some applications, a display device may be viewed in a darkened room where the display is the only source of illumination. In other applications, a display device may be used as an electronic billboard in a bright outdoor environment. Each of these factors—display brightness, dynamic range of the data that a display supports and ambient viewing conditions around the display—may affect a viewer's perception of image data as it is displayed by a device.
“Intensity mapping” has been proposed as a technique to tailor image data for rendering on a display device that accounts for factors such as display brightness, viewing conditions and the like. Techniques have been proposed in ITU_R document 6C/146-E (April 2013), WO 2014/0130343 (2014) and WO 2013/086169 (2013). Although such proposals address the need to adjust image brightness according to these factors, they have certain disadvantages. First, they introduce color shifts that can corrupt some portions of image data. Second, they are computationally expensive.